Category: Amazon Simple Storage Service (S3)

Amazon Relational Database Service (Amazon RDS) for Oracle creates automated snapshots and allows creation of user-initiated manual snapshots in a Region. In addition, Amazon RDS for Oracle supports Oracle native backup tools like Oracle Recovery Manager (RMAN) and Oracle Data Pump. Many organizations spend considerable time and resources to manage and maintain database backups to […]

Migrating the raw data from source systems into a central repository is usually the first step in establishing a data lake. Many systems store source data in relational database tables, therefore a mechanism is required to ingest this data in the data lake and also get some relevant metadata about these tables so that data […]

With more than 45,000 employees in 29 countries, Liberty Mutual is the sixth largest global property and casualty insurer, and currently ranks 71st on the Fortune 100 list of largest corporations in the US. The expectations of customers continue to increase as the pace of change accelerates, the nature and magnitude of risk change, and […]

This is part two of the two-part series of blog posts discussing how to apply smart legal contracts technology to verify delivery conditions with open-source Accord Project and Amazon Quantum Ledger Database service. In the first part we introduced the smart legal contract technology, a sample delivery process, and reviewed the solution to run smart legal contracts on AWS with Accord Project. […]

Smart legal contracts are an emerging technology in the legal tech domain. Their main goal is to make the verification of terms and conditions in legal contracts more efficient. Unlike smart contracts, which are self-running programs in distributed ledger databases (usually in blockchain-based systems), smart legal contracts represent an entire legal contract. They combine a […]

Customers often use Amazon ElastiCache for real-time transactional and analytical use cases. It provides high throughout and low latencies, while meeting a variety of business needs. Because it uses in-memory data structures, typical use cases include database and session caching, as well as leaderboards, gaming and financial trading platforms, social media, and sharing economy apps. […]

In many database applications there arises a need to store large objects, such as files, along with application data. A common approach is to store these files inside the database itself, despite the fact that a database isn’t the architecturally best choice for storing large objects. Primarily, because file system APIs are relatively basic (such […]

You can build highly distributed applications using a multitude of purpose-built databases by decoupling complex applications into smaller pieces, which allows you to choose the right database for the right job. Amazon Aurora is the preferred choice for OLTP workloads. Aurora makes it easy to set up, operate, and scale a relational database in the […]

January 2023: Please refer to Accelerate Amazon DynamoDB data access in AWS Glue jobs using the new AWS Glue DynamoDB Export connector  for more recent updates on using Amazon Glue to extract data from Amazon DynamoDB. Amazon DynamoDB is a key-value and document database that delivers single-digit millisecond performance at any scale. It’s a fully […]

Amazon Relational Database Service (RDS) helps you easily create, operate, and scale a relational database in the cloud. In January 2020, AWS announced the ability to export snapshots from Amazon RDS for MySQL, Amazon RDS for PostgreSQL, Amazon RDS for MariaDB, Amazon Aurora PostgreSQL, and Amazon Aurora MySQL into Amazon S3 in Apache Parquet format. […]